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Recipe: Optimized Caffe* for Deep Learning on Intel® Xeon Phi™ processor x200

The computer learning code Caffe* has been optimized for Intel® Xeon Phi™ processors. This article provides detailed instructions on how to compile and run this Caffe* optimized for Intel® architecture to obtain the best performance on Intel Xeon Phi processors.
Authored by Vamsi Sripathi (Intel) Last updated on 03/21/2019 - 12:40
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Caffe* Scoring Optimization for Intel® Xeon® Processor E5 Series

    In continued efforts to optimize Deep Learning workloads on Intel® architecture, our engineers explore various paths leading to the maximum performance.

Authored by Gennady F. (Blackbelt) Last updated on 03/21/2019 - 12:28
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Using Intel® MPI Library on Intel® Xeon Phi™ Product Family

This document is designed to help users get started writing code and running MPI applications using the Intel® MPI Library on a development platform that includes the Intel® Xeon Phi™ processor.
Authored by Nguyen, Loc Q (Intel) Last updated on 03/21/2019 - 12:00
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Transform Enterprise, HPC & AI, Accelerate Parallel Code

Authored by admin Last updated on 07/06/2019 - 16:15
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TensorFlow* Optimizations on Modern Intel® Architecture

This paper introduces the Artificial Intelligence (AI) community to Intel® optimization for TensorFlow* on Intel® Xeon® and Intel® Xeon Phi™ processor-based CPU platforms.
Authored by Elmoustapha O. (Intel) Last updated on 06/12/2018 - 13:19
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Set Up Intel® Software Optimization for Theano* and Supporting Tools

Get recipes for installing development tools and libraries on various platforms for the Python library.
Authored by Sunny G. (Intel) Last updated on 05/08/2018 - 10:50
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Boosting Deep Learning Training & Inference Performance on Intel® Xeon® and Intel® Xeon Phi™ Processors

In this work we present how, without a single line of code change in the framework, we can further boost the performance for deep learning training by up to 2X and inference by up to 2.7X on top of the current software optimizations available from open source TensorFlow* and Caffe* on Intel® Xeon® processors.
Authored by Vikram S. (Intel) Last updated on 03/21/2019 - 12:40
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Traffic Light Detection Using the TensorFlow* Object Detection API

This case study evaluates the ability of TensorFlow* Object Detection API to solve a real-time problem such as traffic light detection on Intel® Xeon® processor-based CPU machines.
Authored by admin Last updated on 05/08/2018 - 09:30
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Object Detection on Drone Videos using Neon™ Framework

Abstract
Authored by Last updated on 05/08/2018 - 11:39
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Intel® Processors for Deep Learning Training

On November 7, 2017, UC Berkeley, U-Texas, and UC Davis researchers published their results training ResNet-50* in a record time (as of the time of their publication) of 31 minutes and AlexNet* in a record time of 11 minutes on CPUs to state-of-the-art accuracy. These results were obtained on Intel® Xeon® Scalable processors (formerly codename Skylake-SP).
Authored by Andres Rodriguez (Intel) Last updated on 04/15/2018 - 23:05